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Data architecture strategy for data quality

IBM Journey to AI blog

The first generation of data architectures represented by enterprise data warehouse and business intelligence platforms were characterized by thousands of ETL jobs, tables, and reports that only a small group of specialized data engineers understood, resulting in an under-realized positive impact on the business.

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Comparing Tools For Data Processing Pipelines

The MLOps Blog

Data Processing : You need to save the processed data through computations such as aggregation, filtering and sorting. Data Storage : To store this processed data to retrieve it over time – be it a data warehouse or a data lake. Uses secure protocols for data security.

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How and When to Use Dataflows in Power BI

phData

Attach a Common Data Model Folder (preview) When you create a Dataflow from a CDM folder, you can establish a connection to a table authored in the Common Data Model (CDM) format by another application. This path is essential for accessing and manipulating the CDM data within your Dataflow.

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11 Open Source Data Exploration Tools You Need to Know in 2023

ODSC - Open Data Science

With Great Expectations , data teams can express what they “expect” from their data using simple assertions. Great Expectations provides support for different data backends such as flat file formats, SQL databases, Pandas dataframes and Sparks, and comes with built-in notification and data documentation functionality.

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MLOps Landscape in 2023: Top Tools and Platforms

The MLOps Blog

LakeFS LakeFS is an open-source platform that provides data lake versioning and management capabilities. It sits between the data lake and cloud object storage, allowing you to version and control changes to data lakes at scale. Notebook for interactive Python, SQL, and R editors for coding data pipelines.